Pilot symbol aided Minimum Mean-Squared Error (MMSE) channel estimation (which uses only pre-determined or known symbols, commonly referred to in the art as pilot and preamble symbols, in deriving channel estimates) is a well-known method of obtaining channel gain information for symbol decoding in single or multi-carrier systems. For example, the pilot symbol aided MMSE channel estimation method is used in Orthogonal Frequency Division Multiplexing (OFDM) systems such as those that operate in accordance with the Institute of Electrical and Electronics Engineers (IEEE) 802.11a and 802.11g standards.
In some systems, pilot symbol placement and density is designed to enable adequate pilot symbol aided MMSE channel estimation only for low speed applications, for example applications at pedestrian speeds. However, when such systems are operated at higher speeds, a strictly pilot symbol aided channel estimation methodology often proves inadequate. To improve channel estimation for such systems at higher speeds, a decision directed MMSE channel estimation approach may be used. This decision directed approach is also referred to herein as reference symbol aided channel estimation to cover the potential use of both pre-determined as well as regenerated symbols in the channel estimation process. The regenerated reference symbols are typically but not necessarily data symbols.
To implement the reference symbol aided MMSE channel estimation approach using pilot and regenerated data symbols, a receiver in an OFDM system generally includes a MMSE predictive channel estimator to extrapolate the channel gain at a given data symbol location or instant. The MMSE estimator is essentially a linear filter that produces smoothed or predicted channel estimates from a set of “raw” or instantaneous estimates typically at nearby (in the time or frequency sense) symbols. The estimator combines these raw channel estimates with filter coefficients selected from a corresponding set of filter coefficients to predict the channel estimate for the given data symbol.
A set of coefficients can be pre-computed for each data symbol instant and stored in a look-up table. For symmetric delay/Doppler profiles the coefficients are real-valued, providing computational and memory savings. As an improvement, several banks of coefficients pertaining to different channel conditions (e.g., fading rate, signal-to-noise ratio (SNR), etc.) can be provided and the best selected adaptively.
For multi-level constellation systems (e.g., 16 or 64 Quadrature Amplitude Modulation (QAM)), the noise variances of the instantaneous channel estimates depend on the magnitudes of the modulated symbols. To optimize performance in this case, the filter coefficients should ideally be designed as functions of the symbol magnitudes. However, this can lead to a prohibitively large memory requirement. For an N-tap estimator, the number of coefficient sets is equal to MN, where M is the number of symbol magnitudes (e.g., M=3 for 16QAM, and M=9 for 64QAM). For example, a ten tap estimator in a receiver using 64QAM would require 910 different sets of coefficients.
One known method for minimizing coefficient memory is to assume equal symbol magnitude in computing estimator coefficients. However, this approach results in sub-optimal performance for receivers using 16QAM or 64QAM due to what is commonly referred to in the art as “noise enhancement.” In forming the raw channel estimates, noise is enhanced whenever a symbol's squared magnitude is less than the average. For instance, the raw channel estimate for a symbol i is given by gi=vi/pi=(pihi+ni)/pi=hi+(ni/pi), where v is the receiver's demodulator output, p is the symbol value, h is the channel gain and n is the noise. As can be seen, for small magnitudes the effective noise term ni/pi is magnified. Typically, the average noise enhancement is about 2.8 dB for 16QAM and about 4.3 dB for 64QAM.
Thus, there exists a need for a channel estimation method and apparatus that gives improved performance for multi-level constellations without necessitating an impractical amount of memory. It is also desirable that the channel estimation method and apparatus operate with reduced computational complexity, for both multi-level and non-multi-level constellations. It is further desirable that the channel estimation method and apparatus enable higher-speed operation of systems with pilot symbol aided MMSE channel estimation.